de.lmu.ifi.dbs.elki.data.model
Class EMModel<V extends FeatureVector<V,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.data.model.BaseModel
      de.lmu.ifi.dbs.elki.data.model.MeanModel<V>
          de.lmu.ifi.dbs.elki.data.model.EMModel<V>

Type Parameters:

V - Vector type

All Implemented Interfaces:

Model

public class EMModel<V extends FeatureVector<V,?>>
extends MeanModel<V>

Cluster model of an EM cluster, providing a mean and a full covariance Matrix.

Author:

Erich Schubert

Field Summary

private Matrix

covarianceMatrix Cluster covariance matrix

Constructor Summary

EMModel(V mean, Matrix covarianceMatrix)
Constructor.

Method Summary

Matrix	getCovarianceMatrix()
void	setCovarianceMatrix(Matrix covarianceMatrix)
void	writeToText(TextWriterStream out, String label) Implement writeToText as per TextWriteable interface.

Methods inherited from class de.lmu.ifi.dbs.elki.data.model.MeanModel

getMean, setMean

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

covarianceMatrix

private Matrix covarianceMatrix

Cluster covariance matrix

Constructor Detail

EMModel

public EMModel(V mean,
               Matrix covarianceMatrix)

Constructor.

Parameters:

mean - Mean vector

covarianceMatrix - Covariance matrix

Method Detail

writeToText

public void writeToText(TextWriterStream out,
                        String label)

Description copied from class: BaseModel

Implement writeToText as per TextWriteable interface. However BaseModel is not given the interface directly, since it is meant as signal to make Models printable.

Overrides:

writeToText in class BaseModel

Parameters:

out - Output steam

label - Optional label to prefix

getCovarianceMatrix

public Matrix getCovarianceMatrix()

Returns:

covariance matrix

setCovarianceMatrix

public void setCovarianceMatrix(Matrix covarianceMatrix)

Parameters:

covarianceMatrix - covariance matrix